Demo Data from EDBT 2026 / reviewers in the wild / expert
Pak Hay Chan
dblp:178/8618
· DBLP profile ↗
2ranked-venue papers
2as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorTheory of computation · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Graph algorithms and graph theory · 31% Mathematical optimization · 24% Computational complexity · 24% |
Topics — the 11 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization
convex relaxation |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Graph algorithms and graph theory › spectral graph theory
effective resistance |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Graph algorithms and graph theory
graph algorithms |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Computational complexity
hardness of approximation |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Approximation and online algorithms › approximation algorithms
network design |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Mathematical optimization › linear programming relaxation
rounding |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Computational complexity › hardness of approximation
small-set expansion hypothesis |
0.6 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Algorithmic game theory and mechanism design › fair division
envy-freeness |
0.2 | 1 | 2016 | Assignment and Pricing in Roommate Market · AAAI 2016 |
Algorithmic game theory and mechanism design
fair division |
0.2 | 1 | 2016 | Assignment and Pricing in Roommate Market · AAAI 2016 |
Graph algorithms and graph theory › graph algorithms › network flow
minimum-cost flow |
0.2 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Graph algorithms and graph theory › graph algorithms › path problems
shortest path problem |
0.2 | 1 | 2022 | Network Design for s-t Effective Resistance · ACM Trans. Algorithms 2022 |
Methods — techniques the papers use, named apart from their topics
randomized path rounding · 0.6flow decomposition · 0.6dynamic programming · 0.6convex programming relaxation · 0.6pricing scheme · 0.2approximation algorithm · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Network Design for s-t Effective ResistanceabstractWe consider a new problem of designing a network with small s - t effective resistance. In this problem, we are given an undirected graph G = (V,E) , two designated vertices s,t ∈ V , and a budget k . The goal is to choose a subgraph of G with at most k edges to minimize the s - t effective resistance. This problem is an interpolation between the shortest path problem and the minimum cost flow problem and has applications in electrical network design. We present several algorithmic and hardness results for this problem and its variants. On the hardness side, we show that the problem is NP-hard, and the weighted version is hard to approximate within a factor smaller than two assuming the small-set expansion conjecture. On the algorithmic side, we analyze a convex programming relaxation of the problem and design a constant factor approximation algorithm. The key of the rounding algorithm is a randomized path-rounding procedure based on the optimality conditions and a flow decomposition of the fractional solution. We also use dynamic programming to obtain a fully polynomial time approximation scheme when the input graph is a series-parallel graph, with better approximation ratio than the integrality gap of the convex program for these graphs. Pak Hay Chan, Lap Chi Lau, Aaron Schild, Sam Chiu-wai Wong, Hong Zhou 0001 |
ACM Trans. Algorithms | 1 |
| 2016 | Assignment and Pricing in Roommate MarketabstractWe introduce a roommate market model, in which 2n people need to be assigned to n rooms, with two people in each room. Each person has a valuation to each room, as well as a valuation to each of other people as a roommate. Each room has a rent shared by the two people living in the room, and we need to decide who live together in which room and how much each should pay. Various solution concepts on stability and envy-freeness are proposed, with their existence studied and the computational complexity of the corresponding search problems analyzed. In particular, we show that maximizing the social welfare is NP-hard, and we give a polynomial time algorithm that achieves at least 2/3 of the maximum social welfare. Finally, we demonstrate a pricing scheme that can achieve envy-freeness for each room. Pak Hay Chan, Zhengyang Liu 0002, Chihao Zhang 0001, Shengyu Zhang 0002 |
AAAI | 1 |